Upload openchat-3.5-0106_LoRA.yaml
Browse files- openchat-3.5-0106_LoRA.yaml +90 -0
openchat-3.5-0106_LoRA.yaml
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#Training args
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model_name_or_path: openchat/openchat-3.5-0106
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torch_dtype: bfloat16
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use_lora: true
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quantization: 4
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quantization_inference: null
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gradient_checkpointing: true
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force_auto_device_map: false
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use_flash_attention: true
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generation_config: generation_config.json
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stop_words:
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- "<|end_of_turn|>"
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- "GPT4 Correct User:"
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- "GPT4 Correct Assistant:"
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- "</s>"
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- "<s>"
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- "\\n"
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# dataset arguments
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train_datasets:
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- train
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validation_datasets:
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- validation
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test_datasets:
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- test
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max_seq_length: 8192
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generation_max_length: 8192
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prompt_loss_weight: 0.0
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# checkpoint settings
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output_dir: results/finetune/openchat-3.5-0106_Lora
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overwrite_output_dir: true
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load_best_model_at_end: false
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metric_for_best_model: eval_validation_predictions_validation/rouge
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greater_is_better: true
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save_strategy: "epoch"
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save_only_model: true
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save_total_limit: 1
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# evaluation
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do_train: true
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do_eval: true
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do_predict: true
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evaluation_strategy: "epoch"
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predict_with_generate: true
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evaluate_all_checkpoints: true
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# batch size: 2 batch size * 16 gradaccum * 2 GPUs = 64
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per_device_train_batch_size: 8
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per_device_eval_batch_size: 4
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gradient_accumulation_steps: 8
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generation_num_beams: 1
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# optimizer settings
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optim: adamw_torch_fused
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learning_rate: 0.0003
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weight_decay: 0.001
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num_train_epochs: 3
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lr_scheduler_type: cosine
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warmup_ratio: 0.1
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adam_beta1: 0.9
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adam_beta2: 0.95
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adam_epsilon: 1e-12
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# lora settings
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lora_r: 128
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lora_alpha: 256
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lora_dropout: 0.05
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lora_target_modules:
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- all
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# reporting
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logging_strategy: steps
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logging_first_step: true
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logging_steps: 5
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report_to: wandb
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run_name: "openchat-3.5-0106_Lora"
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disable_tqdm: false
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# hub settings
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push_to_hub: false
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resume_from_checkpoint: false
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# performance
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bf16: true
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fp16: false
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torch_compile: false
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ddp_find_unused_parameters: false
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